December 4, 2025
Intro
Digital twins may be an emerging technology, but they’re not new. In the 2000s, digital twins promised a new era of product development and lifecycle management in manufacturing. Digital twins have since spread their wings into industries like automotive, utilities, and even healthcare. More recently, the technology is finding its way into some surprising/interesting spaces like telecommunications and cybersecurity.
Data Centers
Artificial Intelligence (AI) is extremely power intensive. This is due to the volume of data, complex algorithms, continuous operation, and high-performance hardware involved; and it’s driving data centers’ energy consumption (and costs) to unsustainable levels. How can data center operators balance the demands of AI with sustainability? Enter digital twins.
You may be surprised to learn that data centers use as much power as large industries like airlines. AI is both powered by and used within data centers, where AI - or, really AI-powered digital twins - can help mitigate AI’s environmental impact. You read that right: AI can be used to mitigate its own impact through predictive maintenance and even AI-enhanced augmented reality support. That means the ability to predict potential failures, optimize maintenance schedules, and thus reduce downtime.
By digitally replicating almost every asset and service within a facility, data center operators can simulate scenarios and test solutions, producing data-driven insights for refining operations. Digital twins help to better allocate resources, improve cooling systems and more, bringing down energy consumption and reducing carbon emissions without disrupting daily operations.
Let’s consider cooling, which accounts for around 40% of data centers’ total energy consumption. High-density server racks, intensive workloads, and rising power densities are pushing the limits of existing air cooling systems. Digital twins can be used to assess (i.e. simulate) improved cooling methods like liquid cooling, helping operators determine and plan transitions to new, more efficient cooling configurations before making any costly physical changes.
In a similar vein, digital twins can accelerate the adoption of renewable energy, serving as a virtual testing ground for planning the incorporation of renewable energy sources before investing in new infrastructure.
Smarter cooling? Check. Cleaner energy? Check. Digital twins can also help allocate resources more efficiently - even eliminate overprovisioning - by providing insight into resource utilization, including energy usage. This allows for better planning (less waste) as well as improved reporting and compliance. Using digital twins to automate emissions monitoring would reduce errors stemming from manual data entry and ensure regulatory compliance.
Cybersecurity
Digital twins require robust cybersecurity measures. They might also prove a powerful tool for cybersecurity, especially operational technology (OT) cybersecurity, enabling more sophisticated vulnerability detection and defense/response strategies.
What exactly, in this case, are we twinning? Digital twins of real-world assets that support real-time monitoring and predictive analytics can aid in swiftly responding to anomalies and security threats. Proactive risk assessment is another possibility: Using digital twins of an organization’s IT infrastructure (networks, systems and devices) to simulate various cyberattacks in order to pinpoint design flaws and other security gaps.
In all cases, digital twins provide a controlled environment for cybersecurity analysis and testing, helping to identify vulnerabilities before they can be exploited, refine/improve security measures, and even design and validate new security architectures.
IT teams can train with digital twins, simulating different cyberattack scenarios to practice incident response and prepare to deploy new controls, patches or configurations. It’s also possible to study potential cyberthreats, continually updating detection and prevention strategies to match pace with cybercriminals’ increasingly sophisticated efforts.
You might also develop a digital twin of an organization’s “access environment” to simulate and predict changes in identity and access management (IAM). In this way, cybersecurity teams can adapt to evolving business needs without disrupting operations and potentially gain efficiencies by eliminating redundant steps.
Prevention is ideal, of course, but cyber threats are evolving. Adaptability is key–digital twins allow real-time updates and adjustments to security protocols, helping organizations stay ahead of new types of cyberattacks.
From telecom and cybersecurity to urban planning, marketing, trucking, pharmaceuticals, and more–where will digital twins go next?
